Correlation and colocalization of HIF-1α and pimonidazole staining for hypoxia in laryngeal squamous cell carcinomas: A digital, single-cell-based analysis. (May 2022) - Swartz, Justin E.
Highlights: Analysis of hypoxia markers in laryngeal cancer using open-source software is feasible. We found no significant correlation between HIF-1α and PIMO positive cell percentages. There is a moderate correlation between the number of HIF-1α and PIMO positive regions. The overlap between HIF-1α and PIMO positive regions varies widely. Abstract: Objective: Tumor hypoxia results in worse local control and patient survival. We performed a digital, single-cell-based analysis to compare two biomarkers for hypoxia (hypoxia-inducible factor 1-alpha [HIF-1α] and pimonidazole [PIMO]) and their effect on outcome in laryngeal cancer patients treated with accelerated radiotherapy with or without carbogen breathing and nicotinamide (AR versus ARCON). Materials and Methods: Immunohistochemical staining was performed for HIF-1α and PIMO in consecutive sections of 44 laryngeal cancer patients randomized between AR and ARCON. HIF-1α expression and PIMO-binding were correlated using digital image analysis in QuPath. High-density areas for each biomarker were automatically annotated and staining overlap was analyzed. Kaplan-Meier survival analyses for local control, regional control and disease-free survival were performed to predict a response benefit of ARCON over AR alone for each biomarker. Results: 106 Tissue fragments of 44 patients were analyzed. A weak, significant positive correlation was observed between HIF-1α and PIMO positivity on fragment level, but not on patient level. A moderate strength correlation (r = 0.705, p < 0.001) was observed between the number of high-density staining areas for both biomarkers. Staining overlap was poor. HIF-1α expression, PIMO-binding or a combination could not predict a response benefit of ARCON over AR. Conclusion: Digital image analysis to compare positive cell fractions and staining overlap between two hypoxia biomarkers using open-source software is feasible. Our results highlight that there are distinct differences between HIF-1α and PIMO as hypoxia biomarkers and therefore suggest co-existence of different forms of hypoxia within a single tumor.